Prognostic value of p53 protein expression for patients with gastric cancer – a multivariate analysis

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Summary

Mutations in the p53 gene, one of the most common genetic alterations in human cancer, are implicated in tumorigenesis and tumour progression. Although p53 protein expression appears to be correlated to prognosis in patients with malignancy, its prognostic role in gastric cancer has remained controversial. We examined the clinical significance of p53 overexpression in 427 patients with gastric cancer, using multivariate analysis. Tumour sections of gastric cancer tissues from these 427 Japanese patients were stained immunohistochemically with monoclonal antibody PAb1801. The presence of p53 expression was statistically compared with clinicopathological features and post-operative survival, using univariate and multivariate analyses. p53 expression was detected in 38.6% (165 out of 427) of these gastric cancers and immunoreactivity was not observed in normal mucosa adjacent to the tumour. A higher rate of p53 detection was observed among large tumours and in those with a prominent depth of invasion, lymphatic and vascular invasion and lymph node involvement. Prognosis was significantly worse for patients with p53-positive-staining tumours. The 5-year survival rate was 62.5% for patients with p53-negative tumours and 43.3% for those with positive malignancies. p53 expression was a significant prognostic factor for node-positive gastric cancers in subjects undergoing treatment with curative resection, as assessed by Cox regression analysis. Thus, the expression of p53 was closely related to the potential for tumour advance and a poorer post-operative prognosis for patients with gastric cancer.

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  • 16 November 2011

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Correspondence to Y Maehara.

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Maehara, Y., Tomoda, M., Hasuda, S. et al. Prognostic value of p53 protein expression for patients with gastric cancer – a multivariate analysis. Br J Cancer 79, 1255–1261 (1999) doi:10.1038/sj.bjc.6690201

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Keywords

  • gastric cancer
  • p53 expression
  • prognosis
  • multivariate analysis

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